Vishwas Sathish is a PhD-level researcher and engineer with nine years of experience building cutting-edge AI systems that span generative modeling, planning, and applied ML for real-world domains. Currently a Graduate Research Assistant at the Paul G. Allen School, he designs hierarchical generative models and neurally-inspired spatio-temporal abstractions that enable scalable model-based planning across multiple space-time scales. His industry work includes applied science on multimodal visual search and MLLM finetuning as well as leading healthcare AI products—such as a YOLO-based meal classifier and GRU-decay glucose forecaster—that moved research into production and clinical settings. Combining deep math and statistics instincts with practical software delivery, he has a track record of reducing inference and human-review time by orders of magnitude. Based in Seattle, he blends academic rigor with product impact and an explicit interest in advancing safe, human-serving AI toward broader notions of compositionality and transfer.
9 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science and Engineering, Doctor of Philosophy - PhD Computer Science and Engineering at University of Washington
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